MATLAB

说明：  天然地震定位、速度分析matlab程序，适合天然地震研究者、爱好者。(Natural earthquake location, velocity analysis matlab program for natural earthquake researchers, enthusiasts.)

调制指数为0.5的2幅度CPFSK信号的相位轨迹图仿真模型。simulink模型(Modulation index range of 0.5 to 2 CPFSK signal simulation model of the phase trajectories. simulink model)

使用matlab来仿真，是卫星导航电文调制，扩频后，产生.mat文件(Matlab simulation satellite navigation message modulation, spreading generate. Mat file)

此为《MATLAB应用实例精讲》的开源代码，供大家学习参考。(This is MATLAB application examples succinctly, the source code for everyone to learn reference.)

KMEANSK Performs K-means clustering given a list of feature vectors and k The argument k indicates the number of clusters you want the data to be divided into. data_vecs (N*R) is the set of R dimensional feature vectors for N data points. Each row in data_vecs gives the R dimensional vector for a single data point. Each column in data_vecs refers to values for a particular feature vector for all the N data points. The output data_idxs is a N*1 vector of integers telling which cluster number a particular data point belongs to. It also outputs centroids which is a k*R matrix, where each rows gives the vector for the cluster center. If we want to segment a color image i into 5 clusters using spacial and color information, we can use this function as follows:

三相光伏逆变并网的仿真，供做算法研究人员参考，包含光伏电池模块、MPPT模块、BOOST模块、逆变模块。( Three-phase photovoltaic inverter and network simulation, Algorithm for researchers to do reference, PV modules contain, MPPT module, BOOST module, inverter module.)

RLS法20次实验和1次实验的对比分析，调试成功了，可以用(The RLS method 20 experiments and experimental comparative analysis, debugging, you can use)

有序列表的插入，每次添加新数据时，保证整个列表的有序性(Into an ordered list, every time you add new data, to ensure the orderly nature of the entire list)

粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhart博士和kennedy博士发明。源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域(Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), has Dr. Eberhart and Dr. kennedy invention. Deriving from the behavior of birds of prey PSO with genetic algorithm is similar to an iterative optimization-based tools. System initialization for a group of random solutions, through the iterative search for optimal values. But there is no cross-genetic algorithm used (crossover) and mutation (mutation). But the particles in the solution space of the particles to follow the optimal search. In detail the steps after the introduction sections compared with the genetic algorithm, PSO has the advantage of being simple and easy and did not realize many of the parameters need to be adjusted. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications)

MATLAB实现的HOUGH变换直线提取(MATLAB implementation of the HOUGH transform line extraction)